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A New Syllable-lattice Based Approach for Mandarin Spoken Document Retrieval

机译:一种新的基于音节晶格的普通话术语方法检索

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In our Mandarin spoken document retrieval system, the effects of both retrieval source and retrieval model are considered. For the retrieval source, the syllable-lattice is adopted which can ameliorate the effect of speech recognition error on document retrieval. For the retrieval model, the document length prior is combined with Jelinek-Mercer smoothing technique, which is widely applied in text document retrieval model. As far as we know, the combination of syllable lattice and retrieval model based on the document length prior is firstly introduced for spoken document retrieval. Experimental results show that the retrieval performance of lattice-based method outperforms that of 1-best method. Further more, in the retrieval model with the document length priors, lattice-based approach can achieve the best performance, which can improve about 30%.
机译:在我们的普通话中,考虑了检索源和检索模型的影响。对于检索来源,采用音节晶格可以改善语音识别误差对文档检索的影响。对于检索模型,文档长度将与JelineK-Mercer平滑技术相结合,广泛应用于文本文档检索模型。据我们所知,首先引入了基于文档长度的音节格子和检索模型的组合,以便用于口头文档检索。实验结果表明,基于格子的方法的检索性能优于1-最优异的方法。此外,在与文档长度的检索模型中,基于格子的方法可以实现最佳性能,可以提高约30%。

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